Wed.Apr 19, 2023

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Why Learn No Code Machine Learning in 2023?

Analytics Vidhya

Introduction Technologies like machine learning and artificial intelligence have become the talk of the town because of their applicability across organizations of all sizes and domains; and their ability to automate the most complex tasks. It was only in the reinvention of backpropagation in the mid-1980s that they were deemed successful sheerly because of the […] The post Why Learn No Code Machine Learning in 2023?

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Make Better Decisions with Collaborative Analytics

David Menninger's Analyst Perspectives

In my perspective on decision intelligence , I lamented the fact that business intelligence technologies have left the rest of the exercise to the reader for too long. Making a decision is a process that involves many steps and many people. Decision-making is so complicated and divorced from day-to-day business processes that organizations have had to create entirely separate teams to focus on the analytics and data to support it.

Analytics 276
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DinoV2: Most Advanced Self-Taught Vision Model by Meta

Analytics Vidhya

Meta AI has announced the launch of DinoV2, an open-source, self-supervised learning model. It is a vision transformer model for computer vision tasks, built upon the success of its predecessor, DINO. The innovative model delivers robust performance and does not require fine-tuning, setting it apart from other similar models, such as CLIP. Also Read: Microsoft […] The post DinoV2: Most Advanced Self-Taught Vision Model by Meta appeared first on Analytics Vidhya.

Modeling 344
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CIO Fletcher Previn on designing the future of work

CIO Business Intelligence

It has been three years since COVID sent us into remote work, and we now find ourselves with a new challenge: employees who have never met in person. The hybrid work paradigm has exposed the importance of getting in front of evolving changes in the way employees will work together in the future, accelerating IT leaders’ need not only to address the impact of hybrid work and sharpen their tech strategies to support it , but also to help shape the future workplace culture, in large part through e

Strategy 140
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From Developer Experience to Product Experience: How a Shared Focus Fuels Product Success

Speaker: Anne Steiner and David Laribee

As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.

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Tensorflow XLA: The Fusion Compiler for Tensorflow

Analytics Vidhya

Introduction Tensorflow XLA (Accelerated Linear Algebra) is a compiler that can boost the execution speed of tensorflow kernels. This compiler optimizes kernels related to GEMM (generic matrix multiplications), activations, and other linear algebra computations. While executing models built with a Tensorflow core (or Keras), tensorflow computes the kernels individually through the executor on a specific […] The post Tensorflow XLA: The Fusion Compiler for Tensorflow appeared first on Analy

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How to Get Hired as Data Scientist in the GPT-4 Era

KDnuggets

We will be focusing on statistics, core data science concepts, NLP, prompt engineering, data science portfolio, interview preparation, and AIOps.

More Trending

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The power players of retail transformation: IoT, 5G, and AI/ML on Microsoft Cloud

CIO Business Intelligence

Thanks to cloud, Internet of Things (IoT), and 5G technologies, every link in the retail supply chain is becoming more tightly integrated. These technologies are also allowing retailers to capture and gather insights from more and more data – with a big assist from artificial intelligence (AI) and machine learning (ML) technologies – to become more efficient and achieve evolving sustainability goals.

IoT 105
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More Profound than Fire or Electricity: Google CEO Sundar Pichai on AI Developments

Analytics Vidhya

The invention of fire has been one of the most revolutionary developments for humankind. Similarly, Alphabet and Google CEO Sundar Pichai believes that artificial intelligence (AI) and its development will be just as significant to human history. Sundar Pichai has long regarded AI as the most profound technology humanity is developing. “I’ve always thought of […] The post More Profound than Fire or Electricity: Google CEO Sundar Pichai on AI Developments appeared first on Analy

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Top considerations for data modernization initiatives

CIO Business Intelligence

Most organizations are already well under way with their digital transformation journeys, particularly data modernization. For most companies, the drive for data modernization is attributed to the massive growth of data and a business goal to harness as much data as possible to unlock its potential in transformative ways. Adopting cloud-based solutions is, perhaps, one of the most popular means of modernizing.

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The End of the Giant AI Models Era: OpenAI CEO Warns Scaling Era Is Over

Analytics Vidhya

OpenAI, the tech startup known for developing the cutting-edge natural language processing algorithm ChatGPT, has warned that the research strategy that led to the development of the AI model has reached its limits. The OpenAI’s CEO, Sam Altman, said during an event held at the Massachusetts Institute of Technology that future advances would no longer […] The post The End of the Giant AI Models Era: OpenAI CEO Warns Scaling Era Is Over appeared first on Analytics Vidhya.

Modeling 329
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Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.

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Cleaning Up Costs: Avaya and Stemmer Distribution

CIO Business Intelligence

Stemmer Distribution, the largest French company to provide dental products to healthcare professionals since 1978, was able to reduce costs while improving their customer experience with the help of Avaya. With 250 employees and 14 companies across six sites, Stemmer needed a flexible and fluid communication solution for their customers as the brand experienced a high level of growth over the decades; Avaya was the solutions provider to create the strategy needed to achieve this goal.

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Find Out the Difference Between Big Data and Data Science!

Analytics Vidhya

It’s estimated that by 2025, global data creation will reach a mind-boggling 463 exabytes per day. As our world becomes increasingly data-driven, the combination of Big Data and Data Science promises exciting new opportunities and breakthroughs in various fields. Big Data vs Data Science can be confusing owing to their operations on data. However, there […] The post Find Out the Difference Between Big Data and Data Science!

Big Data 329
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Automate discovery of data relationships using ML and Amazon Neptune graph technology

AWS Big Data

Data mesh is a new approach to data management. Companies across industries are using a data mesh to decentralize data management to improve data agility and get value from data. However, when a data producer shares data products on a data mesh self-serve web portal, it’s neither intuitive nor easy for a data consumer to know which data products they can join to create new insights.

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How Long Does It Really Take to Learn Python?

Analytics Vidhya

Introduction One of the most widely used programming languages today, Python’s popularity is rising for all good reasons. It is a beginner-friendly yet highly potential programming language used for various tasks across numerous industries, such as web development, data analysis, machine learning, and artificial intelligence. In fact, as per a recent Stack Overflow survey, over […] The post How Long Does It Really Take to Learn Python?

IT 299
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The Path to Product Excellence: Avoiding Common Pitfalls and Enhancing Communication

Speaker: David Bard, Principal at VP Product Coaching

In the fast-paced world of digital innovation, success is often accompanied by a multitude of challenges - like the pitfalls lurking at every turn, threatening to derail the most promising projects. But fret not, this webinar is your key to effective product development! Join us for an enlightening session to empower you to lead your team to greater heights.

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KDnuggets News, April 19: AutoGPT: Everything You Need To Know • 10 Websites to Get Amazing Data for Data Science Projects

KDnuggets

AutoGPT: Everything You Need To Know • 10 Websites to Get Amazing Data for Data Science Projects • 6 ChatGPT mind-blowing extensions to use it anywhere • Mastering Generative AI and Prompt Engineering: A Free eBook • Baby AGI: The Birth of a Fully Autonomous AI

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Predicting Site EUI Using Machine Learning

Analytics Vidhya

Introduction According to a report by the International Energy Agency (IEA), the lifecycle of buildings from construction to demolition was responsible for 37% of global energy-related and process-related CO2 emissions in 2020. Yet it is possible to drastically reduce buildings’ energy consumption by combining easy-to-implement fixes and state-of-the-art strategies.

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Accelerate HiveQL with Oozie to Spark SQL migration on Amazon EMR

AWS Big Data

Many customers run big data workloads such as extract, transform, and load (ETL) on Apache Hive to create a data warehouse on Hadoop. Apache Hive has performed pretty well for a long time. But with advancements in infrastructure such as cloud computing and multicore machines with large RAM, Apache Spark started to gain visibility by performing better than Apache Hive.

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Weak AI vs Strong AI: Exploring Key Differences and Future Potential of AI

Analytics Vidhya

Strong AI and Weak AI are two fascinating branches of artificial intelligence that capture our imagination. Strong AI, like a smart character from a sci-fi movie, could think, learn, and perform tasks just like humans. On the other hand, Weak AI, the kind we encounter daily, focuses on doing one job well, such as recommending […] The post Weak AI vs Strong AI: Exploring Key Differences and Future Potential of AI appeared first on Analytics Vidhya.

Analytics 264
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How to Build an Experimentation Culture for Data-Driven Product Development

Speaker: Margaret-Ann Seger, Head of Product, Statsig

Experimentation is often seen as an aspirational practice, especially at smaller, fast-moving companies who are strapped for time and resources. So, how can you get your team making decisions in a more data-driven way while continuing to remain lean and maintaining ship velocity? In this webinar, Margaret-Ann Seger, Head of Product at Statsig, will teach you how to build an experimentation culture from the ground-up, graduating from just getting started with data-driven development to operating

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Supervised vs. Unsupervised Machine Learning: Use Cases & Examples

Dataiku

One of the most fundamental concepts to master when getting up to speed with machine learning basics is supervised vs. unsupervised machine learning. This blog post provides a brief rundown, visuals, and a few examples of supervised and unsupervised machine learning to take your ML knowledge to the next level.

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Discovering Data Monetization Opportunities in Financial Services

Cloudera

Data has become an essential driver for new monetization initiatives in the financial services industry. With the vast amount of data collected from customers, transactions, and market movements, among other sources, this abundance offers tremendous potential for financial institutions to extract valuable insights that can inform business decisions, improve customer service, and create new revenue streams.

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Explore LLMs Easily on Your Laptop with openplayground

KDnuggets

Use simple UI to experiment with various renowned large language models.

Modeling 114
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Oracle adds AI, automation capabilities to SCM, HCM Fusion apps

CIO Business Intelligence

Oracle on Wednesday said it is adding new AI and automation capabilities to its Fusion Supply Chain Management (SCM) and Fusion Human Capital Management (HCM) suites to help enterprises increase efficiency across divisions. The updates to the SCM suite, which have been made generally available, include an AI-based planning tool, an enhanced quote-to-cash process for Fusion applications, and new rebate management capabilities.

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Reimagined: Building Products with Generative AI

“Reimagined: Building Products with Generative AI” is an extensive guide for integrating generative AI into product strategy and careers featuring over 150 real-world examples, 30 case studies, and 20+ frameworks, and endorsed by over 20 leading AI and product executives, inventors, entrepreneurs, and researchers.

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Embracing digital transformation: the future of manufacturing efficiency

3AG Systems

In recent years, traditional manufacturing methodologies have reached a plateau, offering diminishing returns as the industry becomes more complex and competitive. The need for digital transformation in the manufacturing sector is more pressing than ever, with businesses striving to stay ahead of the curve and maximize their efficiency. This article will discuss the importance of APIs, best practices for transforming the manufacturing value chain, top digital technologies for manufacturing effic

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Will Taiwan be the next supply chain bottleneck for IT?

CIO Business Intelligence

Taiwan’s semiconductor factories, the source of many of the chips used in the world’s PCs, servers, and mobile phones, operate under a constant threat of disruption. The threats are both geological (earthquakes frequently force high-tech plants to shut down despite them being built to withstand seismic shocks) and geopolitical: China considers Taiwan to be part of its territory and has repeatedly said it aspires to the “complete reunification of the motherland.

IT 52
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Get maximum value out of your cloud data warehouse with Amazon Redshift

AWS Big Data

Every day, customers are challenged with how to manage their growing data volumes and operational costs to unlock the value of data for timely insights and innovation, while maintaining consistent performance. Data creation, consumption, and storage are predicted to grow to 175 zettabytes by 2025, forecasted by the 2022 IDC Global DataSphere report.

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How a water technology company overcame massive data problems with ActionKPI and IBM

IBM Big Data Hub

Access to clean water is essential for the survival and growth of humans, animals and crops. Water technology companies worldwide provide innovative solutions to supply, conserve and protect water throughout the highly complex and technical water cycle of collection, treatment, distribution, reuse and disposal. After a series of international acquisitions, a leading water technology company formed an Assessment Services division to provide water infrastructure services to their customers.

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Entity Resolution Checklist: What to Consider When Evaluating Options

Are you trying to decide which entity resolution capabilities you need? It can be confusing to determine which features are most important for your project. And sometimes key features are overlooked. Get the Entity Resolution Evaluation Checklist to make sure you’ve thought of everything to make your project a success! The list was created by Senzing’s team of leading entity resolution experts, based on their real-world experience.

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Five recommendations for federal agencies to use the cloud to accelerate modernization

IBM Big Data Hub

One of the most distinguishing things about our federal government is its broad scope of services. No other institution is responsible for doing so much for so many, so quickly, in an ever-changing landscape. No other institution must respond simultaneously to such a breadth of challenges that have only been amplified over the last few years. In response to the COVID-19 crisis, many federal agencies kicked their digital transformations into high gear to help enhance public services, embrace a re

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A partnership perspective on government cloud security

IBM Big Data Hub

One of the most distinguishing things about our federal government is its broad scope of services. No other institution is responsible for doing so much for so many, so quickly, in an ever-changing landscape. No other institution must respond simultaneously to such a breadth of challenges that have only been amplified over the last few years. In response to the COVID-19 crisis, many federal agencies kicked their digital transformations into high gear to help enhance public services, embrace a re